摘要
为研究山区高速公路伤害和死亡事故的致因因素,利用故障树建立伤亡事故的贝叶斯网络模型,分别从人、车、路、环境4个方面分析事故影响因素,通过推理和计算可得出相应的发生概率.考虑故障树模型欠缺多态性、相关性和不确定性,提出改进的山区高速公路贝叶斯模型.研究发现:在受伤事故中,车辆因素和驾驶员因素占比最大,其次为道路和环境因素;在死亡事故中,道路因素占比相较于伤害事故增大,明显大于驾驶员因素;其中车辆类型为大型车、夜间无照明和超载3个致因因素导致伤亡事故的可能性增大最为显著.提取危险程度较高的影响因素并提出交通安全改善建议,对山区高速公路交通安全的改善治理工作具有重要意义.
In order to study the contributing factors of injury and fatal crashes on mountainous freeways,a Bayesian network model of injury and death accident is established by using the fault tree method.The influencing factors of crashes are analyzed from four aspects:human,vehicle,road and environment.The corresponding probability can be obtained by reasoning and calculation.Considering the lack of polymorphism,correlation and uncertainty in fault tree model,this study has proposed an improved Bayesian model for crashes occurred on mountainous freeways.It is found that the proportion of vehicle and driver factors is the largest,followed by road and environment factors for injury crashes;for fatal crashes,the proportion of road factor is larger than injury crashes,which is significantly larger than the driver factor;among them,the probability of crashes caused by three factors of vehicle type is the largest.In view of the prominent influencing factors of injury and fatal crashes,this study has proposed the corresponding safety improvement measures,which are of great significance to the improvement and management of traffic safety of mountainous freeways.
作者
柳昕汝
潘晨月
王浩
吴佩洁
孟祥海
LIU Xinru;PAN Chenyue;WANG Hao;WU Peijie;MENG Xianghai(School of Transportation Science and Engineering,Harbin Institute of Technology,Harbin 150090,China)
出处
《交通工程》
2020年第3期7-13,共7页
Journal of Transportation Engineering
关键词
山区高速公路
伤亡事故
贝叶斯网络
三角模糊数
mountainous freeways
injury and fatal crashes
Bayesian network
triangular fuzzy number